Optical character recognition (OCR) consists of recognizing a string of characters in an image and returning a corresponding string of characters (e.g., in text form). OCR has a wide range of applications including the recognition of vehicle license plate numbers (e.g., for use in automated traffic law enforcement, surveillance, access control, tolls, etc.), the recognition of serial numbers on parts in an automated manufacturing environment, the recognition of labels on packages (e.g., pharmaceutical packaging, food and beverage packaging, household and personal products packaging, etc.), and various document analysis applications.
Various types of applications and scenes include images with dot text in which characters of a string are comprised of a set of dots. The expiration date of foods and medicines, the product number of goods, and advertisement lamp boxes with LEDs are examples of images and scenes that would include dot text. Optical character recognition of dot text has several challenges as it involves reading dot text in images with non-uniform dot spacing, deformed, skewed and touching characters, rotated text strings, varying contrast, uneven backgrounds and/or other anomalies.